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An improved decision tree algorithm and its application in maize seed breeding

机译:改进的决策树算法及其在玉米育种中的应用

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The application of information technology in agriculture accelerates the digitization of agriculture information. How to analyze mass of agriculture data and reveal inherent knowledge are becoming new research points. Effective application of data mining technology can achieve this purpose. This paper presents a new improved CA algorithm based on traditional decision tree method. It introduces a pretreatment theory about double dimension reduction which can deal with large and high-scale datasets. By using CA algorithm in maize seed breeding, we can analyze the potential rules and find useful information from it to direct the growth of maize. The experiments show the improved CA algorithm can obtain more intuitive and efficient information.
机译:信息技术在农业中的应用加速了农业信息的数字化。如何分析大量农业数据并揭示内在知识成为新的研究重点。有效地应用数据挖掘技术可以达到这一目的。本文提出了一种基于传统决策树方法的改进的CA算法。它介绍了有关二维缩减的预处理理论,该理论可以处理大型和大规模数据集。通过在玉米种子育种中使用CA算法,我们可以分析潜在的规则并从中找到有用的信息来指导玉米的生长。实验表明,改进的CA算法可以获取更加直观,高效的信息。

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